The field of the invention is systems and methods for determining cardiac functionality within a living subject, and more particularly, to systems and methods for determining cardiac functionality from four-dimensional imaging data.
In the past few years, many non-invasive techniques for measuring blood flow and cardiac function in living subjects have been developed. Many of these techniques have particularly focused on determining the dynamic behavior of the left and right ventricles. Blood flow (a quantitative measure of blood flow through vessels), cardiac ejection fraction (the ratio of ventricle chamber volume between full dilation and full contraction), total cardiac output, and cardiac enlargement are parameters of interest which are significant in determining cardiac disease and failure.
Various imaging modalities have been used to determine these parameters, including ultrasound, X-ray and computed axial tomography (CAT) with contrast agents, and nuclear magnetic resonance (NMR) imaging. Prior-art methods for determining cardiac chamber volumes, for instance, involve using NMR to create four-dimensional (4-D) representations of the heart (i.e., three spatial dimensions and time). The determination of cardiac chamber volume requires multiple (e.g., 10 to 14) image slices to be created in order to obtain a full three-dimensional (3-D) image of the heart.
The various configurations of the heart in its cycle of dilation and contraction are referred to as phases, which include the extremes of end of diastole and end of systole. Synchronizing information obtained from an electrocardiogram (ECG) is used either to trigger the evolution of the sequences of the desired phases, or as a means for sorting of magnetic resonance (MR) signal samples obtained in a free-running fashion. In order to get complete information regarding cardiac function throughout an entire cardiac cycle, a full set of image slices typically are obtained at about 16 to 24 phases in the cardiac cycle.
In most clinical settings, prior-art methods of determining cardiac functionality involve an operator manually tracing, on a computer screen, the region of interest (ROI) (e.g., the boundary of the left ventricle) within each slice of data obtained at all cardiac phases of interest. A typical expert would require about 1.5 to 2 hours to segment 10 to 14 image slices obtained at 16 to 24 phases in the cardiac cycle. Because of the interaction time of the operator, these methods are not extremely efficient. Also, because the boundary between the inside of the chamber and the chamber wall may be obscure due to inadequate contrast, these techniques tend to be inaccurate. In addition, the results are difficult to reproduce because of the variation in the criteria used to manually trace the ROI from image to image, day to day, and operator to operator.
Other, more efficient techniques have been developed in which a gradient data set is constructed from image data indicating the magnitude of spatial changes in the image data set, and then an operator selects a number of sample points over various tissue classes of interest. Further processing results in identification of solid structures, which may indicate the internal volume of cardiac chambers. For example, U.S. Pat. Nos. 5,433,199 and 5,458,126, to Cline et al., entitled xe2x80x9cCardiac Functional Analysis System Employing Gradient Image Segmentation,xe2x80x9d both assigned to the same assignee as the present application, describe such techniques. Although these techniques are effective, they also require a significant amount of operator interaction, thus leading to potential problems of inaccuracy, reproducibility, and inefficiency.
What is needed is an accurate, reproducible, and efficient method and apparatus for in vivo measurement of cardiac function. What is further needed is a method and apparatus for 4-D cardiac analysis which is fully automatic, thus eliminating the need for operator interaction.
The method and apparatus of the preferred embodiment provide the ability to produce accurate and reproducible cardiac images without significant operator interaction. An apparatus performs a method that first acquires a set of image data, where the image data includes intensity values for four-dimensional voxels within a region of interest. Next, a seed voxel is identified from the four-dimensional voxels, and neighbor voxels to the seed voxel are also identified. For each of the neighbor voxels, a determination is made whether an intensity value corresponding to each neighbor voxel indicates that the voxel is likely to correspond to blood or to muscle tissue. For the set of the neighbor voxels having the intensity values that are likely to correspond to blood, new neighbors are determined. The steps of determining whether the voxel intensity value indicates blood or muscle tissue and determining new neighbors are repeated until all voxels of interest have been evaluated, resulting in a final set of voxels. Each voxel of the final set of voxels has an intensity value that is likely to correspond to blood. One or more cardiac images are then reconstructed from the final set of voxels.